Improved generative adversarial networks using the total gradient loss for the resolution enhancement of fluorescence images.
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ABSTRACT:
SUBMITTER: Zhang C
PROVIDER: S-EPMC6757480 | biostudies-literature | 2019 Sep
REPOSITORIES: biostudies-literature
Publications
Improved generative adversarial networks using the total gradient loss for the resolution enhancement of fluorescence images.
Zhang Chong C Wang Kun K An Yu Y He Kunshan K Tong Tong T Tian Jie J
Biomedical optics express 20190822 9
Because of the optical properties of medical fluorescence images (FIs) and hardware limitations, light scattering and diffraction constrain the image quality and resolution. In contrast to device-based approaches, we developed a post-processing method for FI resolution enhancement by employing improved generative adversarial networks. To overcome the drawback of fake texture generation, we proposed total gradient loss for network training. Fine-tuning training procedure was applied to further im ...[more]
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